节点文献
企业仓库拣货路径优化及系统设计研究
【作者】 杨明；
【作者基本信息】 上海交通大学 ， 物流工程， 2008， 硕士
【摘要】 随着经济全球化、市场一体化、信息电子化的发展,物流活动呈现出服务全程化、供应链过程一体化、社会化、管理信息化的特征。为了保证社会经济活动和企业生产顺利进行,并取得良好的经济效益,物流作为“供”、“需”之间有机衔接的桥梁,其地位也日益显著。而在物流系统中起着承上启下作用的物料拣货系统则直接影响着整个物流系统的正常高效的运作,自动分拣机、自动化立体仓库、信息处理及通讯自动化等物流技术已广泛应用于各个流通领域。本文研究了企业仓库物料拣货路径优化及控制系统的设计,通过运用订单分批、路径优化和智能化物料拣货系统的方法,达到提高物料拣货系统的柔性化和高效化,进而降低成本,提高客户满意度,提高企业的物流运营效益,满足企业生产和社会经济活动的需求。因此,本研究不仅有经济效益,还有较深远的社会效益。本研究主要包括四个方面的研究内容:(1)根据分拣方式的不同,讨论研究了拣货系统的类型、主要特点和构成,以及智能化拣货系统的工作原理,并研究了分拣系统的控制实现过程。(2)研究了智能化物料拣货系统拣货路径优化的方向,探讨了作业调度策略与拣货路径优化方法,重点研究了神经网络在拣货作业路径优化中的应用。同时,讨论了拣选方案效率提升的策略,包括影响仓储拣货作业效率的主要因素,多任务拣货操作方式及其流程。(3)研究探讨了智能化拣货系统中控制系统的构建,并设计了基于射频识别技术的零件分拣系统。(4)最后,通过实例对于拣货系统各优化改进方案和原有方案进行了对比,验证了运用智能化物料拣货系统可以提高拣货系统的效率,同时改善系统内部各流程之间的关系。
【Abstract】 With the development of economic globalization, market integration and information technology, Logistics activity tends to fully customer service process characters, more and more socialization and information technology requirements. To secure successful running and achieving to excellent enterprise and social economic efforts, Logistics becomes more and more importance as a bridge between‘supply’and‘demand’. As a key process of Logistics system, picking up system is a very important role and its’efforts impact to the whole logistics operation. More and more advanced logistics technology are used into all processes in supply chain, such as automatic picking machine, automated storage and retrieval system (AS/RS) warehouse, automated telecom and electric data interface etc.. This study analyzed optimizations of materials picking route and control system designation, through order management, routes reengineering and intelligent logistics control system, to improve flexibility and efficiency in logistics operation system, reduce operating cost, improve customer service satisfaction rate and the enterprise logistics operating efficiency, and achieve the requirements of enterprise and social economic activities. So this study not only has economic benefits but also has deeply social benefits.This study includes four parts. Firstly, based on the different picking methods, studied some kinds of intelligent picking system, their characters and components, operating principles and controlling processes. Secondly, this study analyzed the optimization of picking processes with intelligent picking system, planning operation system and pick up routing selection system, especially studied the Neural network method. And this study discussed some options to improve picking efficiency too, including major elements which may impact the picking efficiency, operating models and processes for multi tasks etc. Thirdly, this study analyzed how to setup the controlling system with information technology for intelligent picking system and using radio frequency identification technology into picking system. Finally, this study took a case study to inditify and valid the efforts for above studies.In general, through cases study with intelligent picking up system, we known intelligent picking up system can improve the flexibility and efficiencys, and can optimize the relationship among each processes in picking up system. Implementing intelligent identification information into picking system can help and improve operating efficiency and efforts.